Course content:
1. Basic terms and properties of time series.
2. Dynamics of economic time series. Graphical analysis of time series.
3. Transformation of economic time series, substitution of missing values, outliers and extreme values.
4. Classical model of economic time series (trend, cycle, seasonality).
5. Basic trend models. Trend approximation by mathematical functions.
6. Basic models of seasonal components, seasonal adjustment methods.
7. Verification of estimated model.
8. Adaptive models of economic time series. Moving averages.
9. Exponential smoothing.
10. Principles of forecast construction and prediction quality criteria.
11. Basics of the Box-Jenkins methodology.
12. Model construction in Box-Jenkins methodology.
13. SARIMA-type seasonal time series linear models.
1. Basic terms and properties of time series.
2. Dynamics of economic time series. Graphical analysis of time series.
3. Transformation of economic time series, substitution of missing values, outliers and extreme values.
4. Classical model of economic time series (trend, cycle, seasonality).
5. Basic trend models. Trend approximation by mathematical functions.
6. Basic models of seasonal components, seasonal adjustment methods.
7. Verification of estimated model.
8. Adaptive models of economic time series. Moving averages.
9. Exponential smoothing.
10. Principles of forecast construction and prediction quality criteria.
11. Basics of the Box-Jenkins methodology.
12. Model construction in Box-Jenkins methodology.
13. SARIMA-type seasonal time series linear models.